Comparing AI Tools for International B2B Partner Search: Gemini, ChatGPT, Grok, Mistral, Deepseek, and Copilot

Online search for initial understanding and collecting information on local partners for your international market expansion is a good solution. However, you should do it correctly by focusing on these key factors:

1. A well-defined Ideal Client Profile (ICP): The more precise the ICP, the better the AI can understand the target partner type.
2. Keyword generation in the local language: Effective search relies on relevant industry-specific keywords in both English and the local market’s language.
3. Searching across diverse local databases: AI should be able to leverage local directories, business networks, and marketplaces to find potential partners.

Nowadays, Generative AIs can help you with creating a strong ICP, translation, and keyword generation. However, for a precise search and better results, you need to use expert tools or local consultants.

With these principles in mind, I created a JSON-based prompt designed to automate the partner search process, testing various AI tools on their ability to complete each step effectively.

(comment "send me the prompt" under this article and I will send you the prompt that I created)

Step 1: Understanding the Prompt and Refining the ICP

All AI tools understood the structured JSON prompt and initiated the process by refining the ICP:

• Deepseek and ChatGPT provided a structured approach by asking for additional details, such as company size and certifications, to refine the ICP comprehensively.
• Mistral AI also sought precise information to enrich the ICP, ensuring a tailored approach.
• Grok took a more concise route, offering a simple ICP while inquiring if further development was needed.
• Copilot, however, skipped the ICP refinement step and proceeded directly to keyword generation.

Step 2: Generating the ICP from an Exporter’s Website

To test AI capabilities in understanding a business, I provided the exporter’s website instead of manually defining the ICP:

• Deepseek and Google Gemini delivered the most detailed ICPs, demonstrating strong comprehension of the exporter’s website and business model. Google Gemini excelled in extracting accurate and relevant information, outperforming its competitors in reading and interpreting website content.
• ChatGPT ranked third, generating a good and precise ICP, though with slightly less relevant details related to the exporter’s business.
• Mistral AI, after its recent updates, showed a significant improvement, providing an ICP nearly 10 times better than before—impressive progress!
• Grok excelled in understanding sales channels, though its ICP remained similar in quality to those produced by ChatGPT and Mistral AI.
• Copilot initially skipped the ICP step in the first round. When prompted again, it generated an ICP, but the result was short and lacked highly relevant details based on the exporter’s website.

Step 3: Generating Keywords in Local Language

In this step, the AIs were tested on their ability to generate relevant search keywords in the local language:

• Deepseek delivered the best output, demonstrating an exceptional understanding of the business and its clients. It not only provided highly relevant distributor search keywords in Polish but also suggested keywords for local business directories, e-commerce platforms, and competitor searches, making it the most comprehensive AI for this task.
• Google Gemini also performed well, generating product-related keywords that expanded the scope of search results.
• Grok and ChatGPT produced similar keyword lists—not very extensive but still useful, with over 10 relevant keywords each.
• Copilot was notably limited, providing only five keywords, making it the least effective in this phase.
• Mistral AI performed the worst in keyword generation, failing to grasp the concept of search-focused keywords. It produced a list of one-word keywords, which were too generic and practically unusable for effective partner searches.

Step 4: Conducting the First Search and Creating a Long List of Companies

Initially, all AI tools failed this step as none provided a long list of over 20 companies. This demonstrated a key limitation in their ability to generate comprehensive search results for partner discovery.

To further evaluate their effectiveness, I tested whether the longlisted companies were real and if their website addresses were functional:

• Google Gemini provided a list where all websites were real and had correct addresses. However, while the companies were in the desired industry (cosmetics), they did not fully match the ICP and were mostly online shops. Despite this, Gemini performed the best in ensuring that listed companies actually existed.
• ChatGPT produced a list where 80% of the companies were real, but 20% were fabricated with fake websites. Additionally, some of the companies were not relevant to the ICP.
• Deepseek had similar results to ChatGPT, with 20% of the websites being fake. However, the quality of the listed companies was better. One issue observed was that Deepseek listed several brands from the same company as separate entities, leading to redundancy.
• Grok performed worse than its competitors, with over 30% of the websites being fake and half of the listed companies not aligning with the ICP.
• Copilot initially failed this step, as all websites were fake in the first attempt. However, after insisting on better results, it regenerated a new list, where 60% of the companies were real. While this was an improvement, the companies still lacked full alignment with the ICP. As a result, the scoring system it implemented became somewhat more reliable than before, though still not at the level of other AIs.

This phase exposed major differences in AI reliability for business partner searches, particularly in verifying company authenticity and alignment with ICP criteria. This step tested whether AI tools could retrieve at least 20 relevant companies matching the ICP and keywords:

• Deepseek was the only AI that successfully provided a full list of 20 companies, making it the most effective tool for this step.
• Other AIs, including ChatGPT, Grok, Google Gemini, and Copilot, managed to generate lists of 10 to 15 companies but fell short of the required 20.
• Mistral AI struggled significantly with this task. After multiple attempts, it first declined to conduct searches, later stating that it had reached its web search limit and suggesting an upgrade to a pro version instead. So I tried again this time with Mistral Pro and the results were not bad

For the long list of companies, Mistral AI initially provided only three companies, and after repeated prompts, it increased the list to ten companies—still short of the desired 20-company benchmark. Additionally, 20% of the provided websites were fake.

While most companies listed by Mistral AI were real, they were not highly relevant to the ICP. Instead of listing skincare wholesalers in Poland, it included chemical importers and online shops, missing the mark on the ideal partner type

This phase highlighted major differences in the search capabilities and data retrieval efficiency of the tested AIs.

Step 5: Implementing a Scoring System for Ranking Companies

This step evaluated the analytical power of the AI tools by ordering them to create a scoring system based on multiple factors to rank the longlisted companies according to relevance.

• Grok developed a good scoring system and allowed for the selection of individual companies to receive detailed breakdowns of their scores.
• ChatGPT took an extra step by adding sub-scores to further break down the ranking, a nice improvement, but the final ranking lacked strong relevance.
• Copilot implemented a scoring system, but since almost all of its longlisted companies were fake, the reliability of its scoring system could not be tested.
• Mistral AI It introduced a logical scoring method and attempted to justify its rankings. Despite this, the relevance of its rankings was inconsistent, as it assigned medium scores to high-quality companies and prioritized less relevant businesses over better-matched options.

• Deepseek provided a well-structured table with notes explaining its scoring method. The company rankings were logically assigned, though they were not fully aligned with the given ICP.
• Google Gemini outperformed all competitors, delivering a highly relevant ranking and detailed notes for each company, allowing clear differentiation between them. However, similar to the other AIs, its shortlisted companies were not fully aligned with the ICP.

This phase demonstrated significant variations in the analytical capabilities and scoring reliability of the tested AI tools.